It is not uncommon for an image to have light and/or dark artifacts, such as, dust, scratches, and hair on prints, slides, or negatives being scanned by a scanner, which are commonly generated during creation of the image. These defects may distinctly appear as artifacts that are distinguishable from features of the images. In addition, images often contain other undesirable objects, such as, moles and date stamps, that users would like to remove from the images. As used herein, “undesirable objects” may be considered as referring to the artifacts and/or objects, and “undesirable pixels” may be considered as referring to the pixels forming the artifacts and/or objects, that a user may wish to remove from an image.
The undesirable objects are of increasing concern especially with improved optics and imaging systems that provide images of increased color accuracy and resolution. Further, film photographs are often scanned to provide the film images in digital form, and the scanned images are enlarged for viewing, which also increases the appearance of the undesirable objects.
Conventional computer tools are available to automatically identify some of the undesirable objects by simply locating features in the image having a certain characteristic. Other tools allow users to manually identify the undesirable objects in the image. The locations of the undesirable objects, particularly artifacts, are often summarized in a binary defect map, which marks pixels in an image as defective or non-defective. Alternatively, the artifacts are summarized in a continuous defect map that indicates the individual severities of the pixel defects.
Some conventional computer tools replace the pixels identified as being defective, or otherwise selected for replacement, with replacement values from surrounding pixels. For instance, the computer tools often calculate a value of all of the surrounding pixels and use that value to fill in the desired pixel. One drawback of this type of pixel replacement is that all of the pixels in a particular region will have the same appearance, thereby omitting any textural characteristics present around the pixels selected for replacement.
Other conventional computer tools enable users to manually clone a group of pixels from one location and to add them to the desired pixel locations. While conventional cloning features enable textural characteristics to be added into the desired pixel locations, there are however, various drawbacks associated with the conventional cloning features. For instance, relatively larger sections than were originally intended to be copied are often copied and pasted over the pixels. In addition, cloning from one location of an image to another often results in undesirable results because the overall shades of the source and destination areas typically differ from each other.